CN106361286A - Method and system for recognizing hypnotic state in intelligent aided sleep - Google Patents

Method and system for recognizing hypnotic state in intelligent aided sleep Download PDF

Info

Publication number
CN106361286A
CN106361286A CN201610843660.5A CN201610843660A CN106361286A CN 106361286 A CN106361286 A CN 106361286A CN 201610843660 A CN201610843660 A CN 201610843660A CN 106361286 A CN106361286 A CN 106361286A
Authority
CN
China
Prior art keywords
area
electro
user
hypnosis
detection window
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN201610843660.5A
Other languages
Chinese (zh)
Other versions
CN106361286B (en
Inventor
赵巍
胡静
韩志
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Guangzhou Shiyuan Electronics Thecnology Co Ltd
Original Assignee
Guangzhou Shiyuan Electronics Thecnology Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Guangzhou Shiyuan Electronics Thecnology Co Ltd filed Critical Guangzhou Shiyuan Electronics Thecnology Co Ltd
Priority to CN201610843660.5A priority Critical patent/CN106361286B/en
Publication of CN106361286A publication Critical patent/CN106361286A/en
Application granted granted Critical
Publication of CN106361286B publication Critical patent/CN106361286B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/48—Other medical applications
    • A61B5/4806—Sleep evaluation
    • A61B5/4812—Detecting sleep stages or cycles
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/48—Other medical applications
    • A61B5/486—Bio-feedback

Abstract

The invention relates to a method and a system for recognizing a hypnotic state in intelligent aided sleep. The method comprises the following steps: using a preset detection window to movably detect an electro-oculogram signal waveform within a first time frame after a hypnosis guide word is played; judging to be a first-level hypnosis depth state if the amplitude of the electro-oculogram signal waveform does not exceed the height threshold of the detection window; using an acceleration sensor fixed on an arm of a user to detect an action signal reacted by the user; judging to be a second-level hypnosis depth state if the acceleration sensor does not output an action signal corresponding to an arm raising order within a second time frame; detecting an electroencephalogram signal of the user within a third time frame after target stimulation; and judging to be a third-level hypnosis depth state if a forward-direction waveform occurs in the electroencephalogram signal within the appointed time range. According to the method, the recognition accuracy and the recognition efficiency are improved, and an excellent reference is provided for the hypnosis of the next stage.

Description

Psycheism recognition methodss in intelligent assisting sleep and system
Technical field
The present invention relates to assisting sleep technical field, the psycheism identification in more particularly to a kind of intelligent assisting sleep Method and system.
Background technology
In sleep, human body has carried out the process self loosened and recover.Therefore good sleep is to maintain healthy A primary condition.But due to the reason such as operating pressure is big, daily life system is irregular, result in the sleep matter of part population Amount is not good enough, shows as insomnia, midnight wakes up with a start.
Intelligent assisting sleep is a kind of sleep method of combination modern science and technology, and after subjectss enter psycheism, it is subject to Hint property significantly improves, and can keep close inductive relationship with hypnotist, can be not added with critically accepting its hint instruction.By hypnosis When art is applied to assisting sleep, after hypnotist is by the hypnosis of hypnotist institute, hypnotist sends SLEEP instruction and can make hypnotic Enter sleep state.Compared with pharmaceutical intervention (sleeping pill), less to the side effect of body based on magnetic assisting sleep, than Relatively it is suitable for daily use.
In intelligent assisting sleep, how to identify that hypnosis depth is key factor exactly, need in different hypnosis depth Carry out different hypnosis strategies, guiding user enters sleep, at present for hypnosis depth, can be generally divided into, hypnosis depth May be generally divided into three phases and six grades: hypohypnosis (1-2 level), moderate hypnosis (3-4 level) and depth hypnosis (5-6) Level.For the hypnosis depth of each grade, there is corresponding criterion, special according to the action showing of hypnotic Levy and passed judgment on, for by hypnosis Lai intelligent assisting sleep, correct identification is carried out the premise of next stage hypnosis, But this generally requires hypnotist and just can be judged according to enough experiences, be then difficult to judge for general user, simultaneously this A little sensible format identification hypnosis depth, accuracy is difficult to ensure that, efficiency is low.
Content of the invention
Based on this it is necessary to be directed to the problems referred to above, provide a kind of psycheism recognition methodss in intelligent assisting sleep and System, is capable of the hypnosis depth of relatively accurately identifying user, effectively improves assisting sleep effect.
A kind of psycheism recognition methodss in intelligent assisting sleep, comprising:
In intelligent assisting sleep, play hypnosis introducer to user, detect the electro-ocular signal of described user and obtain right The electro-ocular signal oscillogram answered；
In first time period after playing hypnosis introducer, detect described eye telecommunications using default detection window is mobile Number oscillogram, if the amplitude of described electro-ocular signal oscillogram is not above the height threshold of described detection window, judges described User is currently at first order hypnosis depth state；Wherein, described detection window includes the detection window length setting and height Threshold value；
Play arm to user and lift order, in the second time period after playing arm and lifting order, using being fixed on Acceleration transducer on described user's arm detects the actuating signal of customer responsiveness；
If in described second time period, described acceleration transducer does not export that to lift order corresponding with described arm Actuating signal, then judge that described user is currently at second level hypnosis depth state；
Play target stimulation signal to user, the EEG signals of described user in the 3rd time period after detection target stimulation；
If described EEG signals at the appointed time in the range of positive waveform occurs, judge that described user is currently at the 3rd Level hypnosis depth state.
A kind of psycheism identifying system in intelligent assisting sleep, comprising:
Electro-ocular signal oscillogram acquisition module, for, in intelligent assisting sleep, playing hypnosis introducer, detection to user The electro-ocular signal of described user simultaneously obtains corresponding electro-ocular signal oscillogram；
First hypnosis depth recognition module, in the first time period after playing hypnosis introducer, using default Detection window is mobile to detect described electro-ocular signal oscillogram, if the amplitude of described electro-ocular signal oscillogram is not above described detection The height threshold of window, then judge that described user is currently at first order hypnosis depth state；Wherein, described detection window includes The detection window length setting and height threshold；
Reaction actuating signal detection module, lifts order for playing arm to user, after broadcasting arm lifts order Second time period in, detect the actuating signal of customer responsiveness using the acceleration transducer that is fixed on described user's arm；
Second hypnosis depth recognition module, if for, in described second time period, described acceleration transducer is not defeated Go out and lift the corresponding actuating signal of order with described arm, then judge that described user is currently at second level hypnosis depth state；
Target stimulation test module, for playing target stimulation signal, institute in the 3rd time period after detection target stimulation to user State the EEG signals of user；
3rd hypnosis depth recognition module, if for described EEG signals at the appointed time in the range of positive waveform occurs, Then judge that described user is currently at third level hypnosis depth state.
Psycheism recognition methodss in above-mentioned intelligent assisting sleep and system, during playing hypnosis introducer, lead to Cross the electro-ocular signal of detection user and be identified using detection window, after identification first order hypnosis depth, using acceleration The arm action signal of sensor senses user, identifies second level hypnosis depth, then tests identification using based on auditory stimuluses Third level hypnosis depth, thus realize the identification of three-level hypnosis depth, it is possible to increase identification accuracy, and improves identification effect Rate, provides good reference for execution next stage hypnosis.
Brief description
Fig. 1 is the flow chart of the psycheism recognition methodss in the intelligent assisting sleep of an embodiment；
Fig. 2 is an electro-ocular signal waveform diagram；
Fig. 3 is electro-ocular signal waveform spike area schematic diagram in detection window；
Fig. 4 is the EEG signals oscillogram of detection after multiple target stimulation；
Fig. 5 is the oscillogram after EEG signals oscillogram superposed average；
Fig. 6 is the psycheism identifying system structural representation in the intelligent assisting sleep of an embodiment.
Specific embodiment
The enforcement of the psycheism recognition methodss in the intelligent assisting sleep of the elaboration present invention and system below in conjunction with the accompanying drawings Example.
With reference to shown in Fig. 1, Fig. 1 is the flow process of the psycheism recognition methodss in the intelligent assisting sleep of an embodiment Figure, comprising:
S10, in intelligent assisting sleep, plays hypnosis introducer to user, detects the electro-ocular signal of described user and obtain Take corresponding electro-ocular signal oscillogram；
In this step, usually user, in the case of not falling asleep, carries out intelligent assisting sleep, plays hypnosis to user Introducer, to carry out Sleep intervention to user, using related device, detects the electro-ocular signal of user, and draws corresponding eye electricity Signal waveforms.
In an embodiment, after electro-ocular signal is detected, using data handling equipment, when m- amplitude coordinate system on paint Make corresponding electro-ocular signal oscillogram；Coordinate system can be with the time as transverse axis, with electro-ocular signal amplitude as the longitudinal axis.
In one embodiment, before playing hypnosis introducer to user, also the sleep state of user is detected, When user is detected be non-asleep state, restart hypnosis intervention and identification process.
I.e. before the electro-ocular signal detecting described user, the brain telecommunications that collection user produces during intelligent assisting sleep Number；According to described EEG signals, the sleep state of user is detected, when described user is in non-asleep state, execution is described The step playing hypnosis introducer to user.
S20, in the first time period after playing hypnosis introducer, detects described eye using default detection window is mobile Electric signal waveform figure, if the amplitude of described electro-ocular signal oscillogram is not above the height threshold of described detection window, judges Described user is currently at first order hypnosis depth state；Wherein, described detection window include set detection window length and Height threshold；
In this step, after broadcasting hypnosis introducer is intervened, using detection in setting time (typically taking 30s) Temporally direction of principal axis moves window, and mobile detection electro-ocular signal oscillogram, to detect eyelid active situation, when electro-ocular signal waveform The amplitude of figure is not above described height threshold, that is, the electro-ocular signal waveforms amplitude fluctuating margin being not detected by window exceedes Height threshold, then judge that described user is currently at first order hypnosis depth state.
In one embodiment, for the selection of detection window, need to arrange detection window length and height threshold, that is, exist Detection window along time-axis direction movement is set up on m- amplitude coordinate system when described, and according to nictation speed and electro-ocular signal Amplitude arranges described detection window length and height threshold.
The method of concrete setting can include the following:
A () under normal circumstances, counts quick eye closing action (nictation, i.e. winking reflex) during described user repeatedly blinks Time；Time according to described statistics obtains the nictation speed of described user；
B () counts the maximum of electro-ocular signal amplitude or minima during described user repeatedly blinks；According to described eye electricity The maximum of signal amplitude or the electro-ocular signal amplitude of the minima described user of acquisition；
C () arranges described detection window length according to described nictation speed, and arranged according to described electro-ocular signal amplitude Described height threshold.
In one embodiment, if described nictation speed is [ta, tb], then described detection window length value >=2ta；If Described electro-ocular signal amplitude is m, then described height threshold value≤0.7m.
For example, with reference to shown in Fig. 2, Fig. 2 is an electro-ocular signal waveform diagram, when the nictation speed calculating is 0.3s- 0.4s, electro-ocular signal amplitude is 200uv, then detection window length can be set to 0.6s, and height threshold can be set to 140uv.
In one embodiment it is contemplated that electro-ocular signal waveform is the key character judging nictation, when waveform judges, hold Easily receive the interference in the external world.Therefore, if only relying upon time and amplitude judgement, being easily caused erroneous judgement, therefore, it can further Waveform acuity is judged, to improve identification accuracy.
I.e. when amplitude electro-ocular signal oscillogram is detected exceedes described height threshold, calculate eye telecommunications in detection window The acuity parameter of number waveform spike, if described acuity parameter is less than default acuity parameter threshold, judges institute State user and be currently at first order hypnosis depth state.
In one embodiment, calculate the acuity parameter of electro-ocular signal waveform spike in detection window, can include As follows:
A () calculates upper area area in detection window for the electro-ocular signal waveform and lower area area respectively, calculate Formula is as follows:
area u p = σ i = 1 n ( p m a x - p i )
area d o w n = σ i = 1 n ( p i - p m i n )
In formula, piFor the electro-ocular signal in detection window, pmaxFor the maximum of electro-ocular signal in detection window, pminFor inspection Survey the minima of electro-ocular signal in window, areaupRepresent upper area area, areadownRepresent lower area area；
(b) according to the area of described upper area area and electro-ocular signal waveform spike described in lower area areal calculation, Computing formula is as follows:
blink a r e a = area u p i f area u p < area d o w n area d o w n i f area u p > area d o w n
In formula, blinkareaRepresent the area of spike, if represents and meets condition；
With reference to shown in Fig. 3, Fig. 3 is electro-ocular signal waveform spike area schematic diagram in detection window, the spike in two kinds of directions Upper and lower part region area as illustrated, left figure spike direction upwards, the spike direction of right figure is downward.
C (), according to spike areal calculation acuity parameter, computing formula is as follows:
blinkratio=blinkarea/in-blinkarea
In formula, blinkratioRepresent acuity parameter, in-blinkareaRepresent the area of non-peak position, here point It is ratio between upper area area and lower area area that sharp extent index can also be converted into.
S30, plays arm to user and lifts order, in the second time period after playing arm and lifting order, using solid The acceleration transducer being scheduled on described user's arm detects the actuating signal of customer responsiveness；
In this step, after first order hypnosis depth is detected, play arm to user and lift order, carry out the first order Hypnosis depth detection, the big muscles of detection user are subject to imply situation about being steered, and using acceleration transducer, detect arm Actuating signal.
S40, if in described second time period, described acceleration transducer does not export and lifts order pair with described arm The actuating signal answered, then judge that described user is currently at second level hypnosis depth state；
In this step, if acceleration transducer not output and arm lift in second time period (typically taking 10s) Rise and order corresponding actuating signal, for example, or corresponding sports feel the actuating signal that the rhythm and pace of moving things or other arm actions produce, permissible Think that user reaches second level hypnosis depth.
S50, plays, to user, the music repeatedly inserting target stimulation, detects described in the 3rd time period after each target stimulation The EEG signals of user；
In this step, it is possible to use the p300 signal based on auditory stimuluses, detected under oddball pattern.Example As user carried out with the hint of numeral retardance, user pays close attention to target stimulation, then in the music that will play in hypnosis content Commence play out music, and repeatedly (such as 15 times) the insertion target stimulations when playing music, finally by after the appearance of multiple target stimulation EEG signals in 3rd time period (typically taking 600ms) are overlapped and calculate meansigma methodss.
With reference to shown in Fig. 4, Fig. 4 is the EEG signals oscillogram of detection after multiple target stimulation；Dotted line inframe is the folded of intercepting Plus image section, after superposition is averaging, obtain as shown in figure 5, Fig. 5 is the oscillogram after EEG signals oscillogram superposed average.
S60, if described EEG signals at the appointed time in the range of positive waveform occurs, judge that described user is currently at Third level hypnosis depth state.
In this step, can detect whether an obvious forward wave occurs in the time range of 300ms～500ms Shape, as shown in figure 5, substantially positive waveform, then judges that user is currently at the hypnosis depth of the third level, otherwise does not then reach Arrive.
The scheme of summary embodiment, during playing hypnosis introducer, by the electro-ocular signal of detection user simultaneously It is identified using detection window, after identification first order hypnosis depth, moved using the arm that acceleration transducer detects user Making signal, identify second level hypnosis depth, then testing identification third level hypnosis depth using based on auditory stimuluses, thus realizing The identification of three-level hypnosis depth, it is possible to increase identification accuracy, and improve recognition efficiency, carry for execution next stage hypnosis Supply good reference.
With reference to shown in Fig. 6, Fig. 6 is the psycheism identifying system structural representation in the intelligent assisting sleep of an embodiment Figure, comprising:
Electro-ocular signal oscillogram acquisition module 10, for, in intelligent assisting sleep, playing hypnosis introducer, inspection to user Survey the electro-ocular signal of described user and obtain corresponding electro-ocular signal oscillogram；
First hypnosis depth recognition module 20, in the first time period after playing hypnosis introducer, using default Detection window mobile detect described electro-ocular signal oscillogram, if the amplitude of described electro-ocular signal oscillogram is not above described inspection Survey the height threshold of window, then judge that described user is currently at first order hypnosis depth state；Wherein, described detection window bag Include detection window length and the height threshold of setting；
Reaction actuating signal detection module 30, lifts order for playing arm to user, lifts order playing arm The action letter of customer responsiveness in second time period afterwards, is detected using the acceleration transducer being fixed on described user's arm Number；
Second hypnosis depth recognition module 40, if for, in described second time period, described acceleration transducer does not have Output lifts the corresponding actuating signal of order with described arm, then judge that described user is currently at second level hypnosis depth shape State；
Target stimulation test module 50, for playing target stimulation signal to user, in the 3rd time period after detection target stimulation The EEG signals of described user；
3rd hypnosis depth recognition module 60, if for described EEG signals at the appointed time in the range of forward wave occurs Shape, then judge that described user is currently at third level hypnosis depth state.
Urging in the psycheism identifying system in the intelligent assisting sleep of the present invention and the intelligent assisting sleep of the present invention Dormancy state identification method corresponds, the skill of the embodiment elaboration of the psycheism recognition methodss in above-mentioned intelligent assisting sleep Art feature and its advantage all in the embodiment of the psycheism identifying system intelligent assisting sleep, sound hereby Bright.
Each technical characteristic of embodiment described above can arbitrarily be combined, for making description succinct, not to above-mentioned reality The all possible combination of each technical characteristic applied in example is all described, as long as however, the combination of these technical characteristics is not deposited In contradiction, all it is considered to be the scope of this specification record.
Embodiment described above only have expressed the several embodiments of the present invention, and its description is more concrete and detailed, but simultaneously Can not therefore be construed as limiting the scope of the patent.It should be pointed out that coming for those of ordinary skill in the art Say, without departing from the inventive concept of the premise, some deformation can also be made and improve, these broadly fall into the protection of the present invention Scope.Therefore, the protection domain of patent of the present invention should be defined by claims.

Claims (10)

1. the psycheism recognition methodss in a kind of intelligent assisting sleep are it is characterised in that include:
In intelligent assisting sleep, play hypnosis introducer to user, detect the electro-ocular signal of described user and obtain corresponding Electro-ocular signal oscillogram；
In first time period after playing hypnosis introducer, detect described electro-ocular signal ripple using default detection window is mobile Shape figure, if the amplitude of described electro-ocular signal oscillogram is not above the height threshold of described detection window, judges described user It is currently at first order hypnosis depth state；Wherein, described detection window includes detection window length and the height threshold setting；
Play arm to user and lift order, in the second time period after playing arm and lifting order, described using being fixed on Acceleration transducer on user's arm detects the actuating signal of customer responsiveness；
If in described second time period, described acceleration transducer does not export and lifts the corresponding action of order with described arm Signal, then judge that described user is currently at second level hypnosis depth state；
Play target stimulation signal to user, the EEG signals of described user in the 3rd time period after detection target stimulation；
If described EEG signals at the appointed time in the range of positive waveform occurs, judge that described user is currently at the third level and urges Dormancy depth state.
2. the psycheism recognition methodss in intelligent assisting sleep according to claim 1 are it is characterised in that also include:
When m- amplitude coordinate system on draw described electro-ocular signal oscillogram；
Detection window along time-axis direction movement is set up on m- amplitude coordinate system when described, and according to nictation speed and eye Signal of telecommunication amplitude arranges described detection window length and height threshold.
3. the psycheism recognition methodss in intelligent assisting sleep according to claim 1 are it is characterised in that to user Before playing the step of hypnosis introducer, also include:
The EEG signals that collection user produces during intelligent assisting sleep；
According to described EEG signals, the sleep state of user is detected, when described user is in non-asleep state, execute institute State the step playing hypnosis introducer to user.
4. the psycheism recognition methodss in intelligent assisting sleep according to claim 2 are it is characterised in that described basis The step of nictation speed and the electro-ocular signal amplitude described detection window length of setting and height threshold includes:
Under normal circumstances, count the time of quickly eye closing action during described user repeatedly blinks；According to described statistics when Between obtain the nictation speed of described user；
Count the maximum of electro-ocular signal amplitude during described user repeatedly blinks or minima；According to described electro-ocular signal amplitude Maximum or minima obtain described user electro-ocular signal amplitude；
Described detection window length is arranged according to described nictation speed, and described height is arranged according to described electro-ocular signal amplitude Threshold value.
If 5. the psycheism recognition methodss in intelligent assisting sleep according to claim 1 are it is characterised in that described eye The amplitude of electric signal waveform figure exceedes described height threshold, also includes:
Calculate the acuity parameter of electro-ocular signal waveform spike in detection window, if described acuity parameter is less than default Acuity parameter threshold, judges that described user is currently at first order hypnosis depth state.
6. the psycheism recognition methodss in intelligent assisting sleep according to claim 5 are it is characterised in that described calculating In detection window, the step of the acuity parameter of electro-ocular signal waveform spike includes:
Calculate upper area area in detection window for the electro-ocular signal waveform and lower area area respectively；
Area according to described upper area area and electro-ocular signal waveform spike described in lower area areal calculation；
According to spike areal calculation acuity parameter.
7. the psycheism recognition methodss in intelligent assisting sleep according to claim 6 are it is characterised in that described top The computing formula of region area and lower area area is as follows:
area u p = &sigma; i = 1 n ( p m a x - p i )
area d o w n = &sigma; i = 1 n ( p i - p m i n )
In formula, piFor the electro-ocular signal in detection window, pmaxFor the maximum of electro-ocular signal in detection window, pminFor detecting window The minima of electro-ocular signal, area in mouthfulupRepresent upper area area, areadownRepresent lower area area；
The computing formula of the area of described electro-ocular signal waveform spike is as follows:
blink a r e a = area u p i f area u p < area d o w n area d o w n i f area u p > area d o w n
In formula, blinkareaRepresent the area of spike, if represents and meets condition；
The computing formula of described acuity parameter is as follows:
blinkratio=blinkarea/in-blinkarea
In formula, blinkratioRepresent acuity parameter, in-blinkareaRepresent the area of non-peak position, here sharp journey It is ratio between upper area area and lower area area that degree parameter can also be converted into.
If 8. the psycheism recognition methodss in intelligent assisting sleep according to claim 4 are it is characterised in that described blink Eye speed is [ta, tb], then described detection window length value >=2ta；
If described electro-ocular signal amplitude is m, described height threshold value≤0.7m.
9. the psycheism recognition methodss in intelligent assisting sleep according to claim 1 are it is characterised in that described broadcasting Setting time after hypnosis introducer is 30s, and described second time period is 10s.
10. the psycheism identifying system in a kind of intelligent assisting sleep is it is characterised in that include:
Electro-ocular signal oscillogram acquisition module, for, in intelligent assisting sleep, playing hypnosis introducer to user, detection is described The electro-ocular signal of user simultaneously obtains corresponding electro-ocular signal oscillogram；
First hypnosis depth recognition module, in the first time period after playing hypnosis introducer, using default detection Window is mobile to detect described electro-ocular signal oscillogram, if the amplitude of described electro-ocular signal oscillogram is not above described detection window Height threshold, then judge that described user is currently at first order hypnosis depth state；Wherein, described detection window includes setting Detection window length and height threshold；
Reaction actuating signal detection module, lifts order for playing arm to user, is playing after arm lifts order the The actuating signal of customer responsiveness in two time periods, is detected using the acceleration transducer being fixed on described user's arm；
Second hypnosis depth recognition module, if in described second time period, described acceleration transducer do not export with Described arm lifts the corresponding actuating signal of order, then judge that described user is currently at second level hypnosis depth state；
Target stimulation test module, for playing target stimulation signal, described use in the 3rd time period after detection target stimulation to user The EEG signals at family；
3rd hypnosis depth recognition module, if for described EEG signals at the appointed time in the range of positive waveform occurs, sentence Fixed described user is currently at third level hypnosis depth state.
CN201610843660.5A 2016-09-21 2016-09-21 Hypnosis recognition methods and system in intelligent assisting sleep Active CN106361286B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201610843660.5A CN106361286B (en) 2016-09-21 2016-09-21 Hypnosis recognition methods and system in intelligent assisting sleep

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201610843660.5A CN106361286B (en) 2016-09-21 2016-09-21 Hypnosis recognition methods and system in intelligent assisting sleep

Publications (2)

Publication Number Publication Date
CN106361286A true CN106361286A (en) 2017-02-01
CN106361286B CN106361286B (en) 2019-02-26

Family

ID=57897262

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201610843660.5A Active CN106361286B (en) 2016-09-21 2016-09-21 Hypnosis recognition methods and system in intelligent assisting sleep

Country Status (1)

Country Link
CN (1) CN106361286B (en)

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2002219116A (en) * 2001-01-26 2002-08-06 Matsushita Electric Ind Co Ltd Sleep cycle detector
CN1860987A (en) * 2006-03-28 2006-11-15 北京大学 System for monitoring and intervening sleep and dream, and processing method therefor
TW201350083A (en) * 2012-06-04 2013-12-16 Taidoc Technology Corp Apparatus and method for sleep analysis and EOG sensor thereof
US20150190607A1 (en) * 2014-01-09 2015-07-09 Panasonic Corporation Control method, control device, and eye mask
CN105496356A (en) * 2014-10-08 2016-04-20 精工爱普生株式会社 Sleep state determination apparatus, sleep state determination method, and sleep management system
CN105833411A (en) * 2016-03-03 2016-08-10 太原特玛茹电子科技有限公司 Novel intelligent sleeping-aiding and natural wakening method and device

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2002219116A (en) * 2001-01-26 2002-08-06 Matsushita Electric Ind Co Ltd Sleep cycle detector
CN1860987A (en) * 2006-03-28 2006-11-15 北京大学 System for monitoring and intervening sleep and dream, and processing method therefor
TW201350083A (en) * 2012-06-04 2013-12-16 Taidoc Technology Corp Apparatus and method for sleep analysis and EOG sensor thereof
US20150190607A1 (en) * 2014-01-09 2015-07-09 Panasonic Corporation Control method, control device, and eye mask
CN105496356A (en) * 2014-10-08 2016-04-20 精工爱普生株式会社 Sleep state determination apparatus, sleep state determination method, and sleep management system
CN105833411A (en) * 2016-03-03 2016-08-10 太原特玛茹电子科技有限公司 Novel intelligent sleeping-aiding and natural wakening method and device

Also Published As

Publication number Publication date
CN106361286B (en) 2019-02-26

Similar Documents

Publication Publication Date Title
CN106333673B (en) Hypnosis depth detector
CN101583313B (en) Awake state judging model making device, awake state judging device, and warning device
DE69833656T2 (en) DEVICE FOR DIAGNOSIS OF PULSE WAVES
CN103793058B (en) A kind of active brain-computer interactive system Mental imagery classification of task method and device
CN106178222A (en) Based on magnetic intelligence assisting sleep method and system
DE69728031T2 (en) ORGANISM STATUS MEASURING DEVICE AND RELAXATION STATUS INDICATOR
US7844324B2 (en) Measurement of EEG reactivity
CN105054951B (en) A kind of fatigue driving eeg monitoring method based on frequency of wink identification
CN105496404A (en) Assessment method of auxiliary CRS-R scale auditory shock based on brain-computer interface
JPWO2013035704A1 (en) Dozing detection method and device
CN102526879B (en) Device and system for adaptively adjusting pacing frequency
CN101547643A (en) Device for judging degree of awakening and method for judging degree of awakening
CN106175699B (en) Based on magnetic intelligent assisting sleep equipment
CN1811851A (en) Method for realizing sleep learning and apparatus
CN105266805A (en) Visuoauditory brain-computer interface-based consciousness state detecting method
CN105380618A (en) biological information analyzing system and biological information processing system
CN104586410A (en) Mobile terminal, wearable device and system and method for judging user state
CN103190923A (en) Drowsiness detection method and device thereof
CN106108843A (en) A kind of user of determination sleeps the method and system of duration
CN106963361B (en) Detection method, detection device and the electrocardio equipment of limb leads misconnection
CN105224809A (en) A kind of self-service examination system based on Kinect and method
CN106361330A (en) Method and system for recognizing sleep state in intelligent aided sleep
CN109620158A (en) Method, intelligent terminal and the storage device of Sleep-Monitoring
CN106730236A (en) One kind loosens bootstrap technique, apparatus and system
CN107095645A (en) A kind of sleep-respiratory low pass based on the sound of snoring suspends the diagnostic device of syndrome

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant